VGX Foundation And Honeyland Partner To Offer VGX Rewards For Players

GEORGE TOWN, Cayman Islands, June 12th, 2024/Chainwire/–The VGX Foundation has announced a partnership with popular web3 game Honeyland, offering rewards utilizing the VGX token for their players. VGX is a token that bridges multiple chains and is focused on bridging utility across GameFi and gaming ecosystems. Honeyland is a popular blockchain-based casual strategy game available … Read more

A Novel Framework for Analyzing Economic News Narratives Using GPT-3.5: Results

:::info Authors: (1) Deborah Miori, Mathematical Institute, University of Oxford, Oxford, UK and 2Oxford-Man Institute of Quantitative Finance, Oxford, UK (Corresponding author: Deborah Miori, deborah.miori@maths.ox.ac.uk); (2) Constantin Petrov, Fidelity Investments, London, UK. ::: Table of Links Abstract and Intro Data Framework Results Conclusions, Acknowledgements, and References 4 Results 4.1 Word2vec benchmark We begin by considering … Read more

Doggy AI Presale Reaches Over $101,000 Shortly After Launch

LONDON, United Kingdom, June 12th, 2024/Chainwire/–Doggy AI(DOGYAI)has swiftly accumulated over $101,000 in its presale shortly after launch, and the DOGYAI team sees this as an encouraging start in the meme coin market. Built on the Ethereum blockchain, Doggy AI combines meme culture with advanced AI technology. It aims to attract a broad community by offering … Read more

Trust and Acceptance of Social Robots: Discussion & Conclusion

:::info Author: (1) Katrin Fischer, Annenberg School for Communication at the University of Southern California, Los Angeles (Email: katrinfi@usc.edu); (2) Donggyu Kim, Annenberg School for Communication at the University of Southern California, Los Angeles (Email: donggyuk@usc.edu); (3) Joo-Wha Hong, Marshall School of Business at the University of Southern California, Los Angeles (Email: joowhaho@marshall.usc.edu). ::: Table … Read more

Altura Launches $1M Web 3 Gaming Grant Fund to Empower Developers

Photo credits: Unsplash Web3 gaming isn’t just growing; it’s exploding—transforming player economies and redefining ownership of in-game assets. Barriers? Obliterated. The old narrative? Completely rewritten. How? By leveraging DeFi and innovative blockchain technologies that empower players with real ownership and investment opportunities in their gaming experiences. Altura steps right into the heart of this revolution … Read more

Is This the Robinhood Moment for Memecoins? Discovering the Bolide App

Robinhood has made waves in the casual investment community for being a commission-free, mobile-friendly app that’s made trading accessible to everyone — not just the wealthy or experienced traders. It’s only natural, then, that a similar solution be made available for would-be crypto investors — and it’s vital that this solution is made specifically for the … Read more

An Architect’s Guide to Building Reference Architecture for an AI/ML Datalake

An abbreviated version of this post appeared on The New Stack on March 19th, 2024. In enterprise artificial intelligence, there are two main types of models: discriminative and generative. Discriminative models are used to classify or predict data, while generative models are used to create new data. Even though Generative AI has dominated the news … Read more

Staking Bitcoin? Billions in Bitcoin Bridged as Merlin Brings DeFi to BTC

Bitcoin investors now have new options to earn yield on their holdings through Merlin Chain, a Layer 2 blockchain protocol built for Bitcoin. The platform’s proof-of-stake consensus allows users to stake wrapped bitcoin (M-BTC) and earn staking rewards, similar to how Ethereum users can stake ether. After bridging BTC to the Merlin network, users lock … Read more

Trust and Acceptance of Social Robots: Analysis & Results

:::info Author: (1) Katrin Fischer, Annenberg School for Communication at the University of Southern California, Los Angeles (Email: katrinfi@usc.edu); (2) Donggyu Kim, Annenberg School for Communication at the University of Southern California, Los Angeles (Email: donggyuk@usc.edu); (3) Joo-Wha Hong, Marshall School of Business at the University of Southern California, Los Angeles (Email: joowhaho@marshall.usc.edu). ::: Table … Read more

Pixelverse Secures $5.5M in Funding to Expand Web3 Gaming Ecosystem

Pixelverse, a Seoul-based entertainment studio and game ecosystem, has successfully raised $5.5M in a funding round led by prominent venture capital firms and influential founders from the gaming and Web3 industries. The company plans to utilize the funds to further expand its gaming ecosystem, which has already attracted an impressive 15 million users within its … Read more

Space and Time Opens New Doors for DeFi with Sub-Second ZK Prover, Proof of SQL

Space and Time (SxT), a leading provider of verifiable compute solutions for AI and blockchain integration, has made a significant stride in advancing Web3 technology by releasing Proof of SQL, a high-performance zero-knowledge prover for processing data, under an open software license on GitHub. This groundbreaking development promises to revolutionize the way developers interact with … Read more

An In-Depth Study on Predicting Human Falls Using AI

Human Falling and Movement Classification is a comprehensive system that can be built using machine learning. However, collaboration between machine learning and healthcare paves the path to innovative solutions. In this guide, you will understand in-depth human falling and movement classification, the key technologies used to build throughout the research, a comprehensive view of each … Read more

Deep Neural Networks to Detect and Quantify Lymphoma Lesions: Results

:::info Authors: (1) Shadab Ahamed, University of British Columbia, Vancouver, BC, Canada, BC Cancer Research Institute, Vancouver, BC, Canada. He was also a Mitacs Accelerate Fellow (May 2022 – April 2023) with Microsoft AI for Good Lab, Redmond, WA, USA (e-mail: shadabahamed1996@gmail.com); (2) Yixi Xu, Microsoft AI for Good Lab, Redmond, WA, USA; (3) Claire … Read more

Deep Neural Networks to Detect and Quantify Lymphoma Lesions: Materials and Methods

:::info Authors: (1) Shadab Ahamed, University of British Columbia, Vancouver, BC, Canada, BC Cancer Research Institute, Vancouver, BC, Canada. He was also a Mitacs Accelerate Fellow (May 2022 – April 2023) with Microsoft AI for Good Lab, Redmond, WA, USA (e-mail: shadabahamed1996@gmail.com); (2) Yixi Xu, Microsoft AI for Good Lab, Redmond, WA, USA; (3) Claire … Read more

Deep Neural Networks to Detect and Quantify Lymphoma Lesions: Conclusion and References

:::info Authors: (1) Shadab Ahamed, University of British Columbia, Vancouver, BC, Canada, BC Cancer Research Institute, Vancouver, BC, Canada. He was also a Mitacs Accelerate Fellow (May 2022 – April 2023) with Microsoft AI for Good Lab, Redmond, WA, USA (e-mail: shadabahamed1996@gmail.com); (2) Yixi Xu, Microsoft AI for Good Lab, Redmond, WA, USA; (3) Claire … Read more

Deep Neural Networks to Detect and Quantify Lymphoma Lesions: Related Work

:::info Authors: (1) Shadab Ahamed, University of British Columbia, Vancouver, BC, Canada, BC Cancer Research Institute, Vancouver, BC, Canada. He was also a Mitacs Accelerate Fellow (May 2022 – April 2023) with Microsoft AI for Good Lab, Redmond, WA, USA (e-mail: shadabahamed1996@gmail.com); (2) Yixi Xu, Microsoft AI for Good Lab, Redmond, WA, USA; (3) Claire … Read more

Deep Neural Networks to Detect and Quantify Lymphoma Lesions: Discussion

:::info Authors: (1) Shadab Ahamed, University of British Columbia, Vancouver, BC, Canada, BC Cancer Research Institute, Vancouver, BC, Canada. He was also a Mitacs Accelerate Fellow (May 2022 – April 2023) with Microsoft AI for Good Lab, Redmond, WA, USA (e-mail: shadabahamed1996@gmail.com); (2) Yixi Xu, Microsoft AI for Good Lab, Redmond, WA, USA; (3) Claire … Read more

Deep Neural Networks to Detect and Quantify Lymphoma Lesions: Abstract and Intro

:::info Author: (1) Shadab Ahamed, University of British Columbia, Vancouver, BC, Canada, BC Cancer Research Institute, Vancouver, BC, Canada. He was also a Mitacs Accelerate Fellow (May 2022 – April 2023) with Microsoft AI for Good Lab, Redmond, WA, USA (e-mail: shadabahamed1996@gmail.com); (2) Yixi Xu, Microsoft AI for Good Lab, Redmond, WA, USA; (3) Claire … Read more

Finding AI-Generated Faces in the Wild: Abstract and Intro

:::info Authors: (1) Gonzalo J. Aniano Porcile, LinkedIn; (2) Jack Gindi, LinkedIn; (3) Shivansh Mundra, LinkedIn; (4) James R. Verbus, LinkedIn; (5) Hany Farid, LinkedIn and University of California, Berkeley. ::: Table of Links Abstract and Intro Data sets Model Results Discussion, Acknowledgements, and References Abstract AI-based image generation has continued to rapidly improve, producing … Read more

Finding AI-Generated Faces in the Wild: Discussion, Acknowledgements, and References

:::info Authors: (1) Gonzalo J. Aniano Porcile, LinkedIn; (2) Jack Gindi, LinkedIn; (3) Shivansh Mundra, LinkedIn; (4) James R. Verbus, LinkedIn; (5) Hany Farid, LinkedIn and University of California, Berkeley. ::: Table of Links Abstract and Intro Data sets Model Results Discussion, Acknowledgements, and References 5. Discussion For many image classification problems, large neural models … Read more

Finding AI-Generated Faces in the Wild: Results

:::info Authors: (1) Gonzalo J. Aniano Porcile, LinkedIn; (2) Jack Gindi, LinkedIn; (3) Shivansh Mundra, LinkedIn; (4) James R. Verbus, LinkedIn; (5) Hany Farid, LinkedIn and University of California, Berkeley. ::: Table of Links Abstract and Intro Data sets Model Results Discussion, Acknowledgements, and References 4. Results Our baseline training and evaluation performance is shown … Read more

Finding AI-Generated Faces in the Wild: Data sets

:::info Authors: (1) Gonzalo J. Aniano Porcile, LinkedIn; (2) Jack Gindi, LinkedIn; (3) Shivansh Mundra, LinkedIn; (4) James R. Verbus, LinkedIn; (5) Hany Farid, LinkedIn and University of California, Berkeley. ::: Table of Links Abstract and Intro Data sets Model Results Discussion, Acknowledgements, and References 2. Data Sets Our training and evaluation leverage 18 data … Read more

Finding AI-Generated Faces in the Wild: Model

:::info Authors: (1) Gonzalo J. Aniano Porcile, LinkedIn; (2) Jack Gindi, LinkedIn; (3) Shivansh Mundra, LinkedIn; (4) James R. Verbus, LinkedIn; (5) Hany Farid, LinkedIn and University of California, Berkeley. ::: Table of Links Abstract and Intro Data sets Model Results Discussion, Acknowledgements, and References 3. Model We train a model to distinguish real from … Read more

Blue Chip Crypto Investment – How To Do It Right

In equity investment, a blue chip is a stock that will last for decades and pays consistent yearly dividends. Think Microsoft, Apple, Proctor & Gamble, Coca-Cola, McDonald’s, Johnson and Johnson, etc. Practically too big to fail and very reliable. If they take a price hit, they will bounce back. Many modern investors have moved on … Read more

A Novel Framework for Analyzing Economic News Narratives Using GPT-3.5: Data

:::info Authors: (1) Deborah Miori, Mathematical Institute, University of Oxford, Oxford, UK and 2Oxford-Man Institute of Quantitative Finance, Oxford, UK (Corresponding author: Deborah Miori, deborah.miori@maths.ox.ac.uk); (2) Constantin Petrov, Fidelity Investments, London, UK. ::: Table of Links Abstract and Intro Data Framework Results Conclusions, Acknowledgements, and References 2 Data 2.1 Corpus of news We download a … Read more

How AI Automates Data Scraping and Data Analysis

Over the last few years, AI has revolutionized our lives by not just automating repetitive work but also seemingly developing the ability to “think” like a human being and tap into the creativity pool. Seriously, how many of you have used “Chat-GPT” to compose a poem or used “Suno” for another love song? Maybe it’s … Read more

Limitations, Ethical Considerations, and More: Everything You Need to Know About WikiWebQuestions

:::info Authors: (1) Silei Xu, Computer Science Department, Stanford University Stanford, CA with equal contribution {silei@cs.stanford.edu}; (2) Shicheng Liu, Computer Science Department, Stanford University Stanford, CA with equal contribution {shicheng@cs.stanford.edu}; (3) Theo Culhane, Computer Science Department, Stanford University Stanford, CA {tculhane@cs.stanford.edu}; (4) Elizaveta Pertseva, Computer Science Department, Stanford University Stanford, CA, {pertseva@cs.stanford.edu}; (5) Meng-Hsi Wu, … Read more

Experimenting With QALD-7: Evaluating WikiSP

:::info Authors: (1) Silei Xu, Computer Science Department, Stanford University Stanford, CA with equal contribution {silei@cs.stanford.edu}; (2) Shicheng Liu, Computer Science Department, Stanford University Stanford, CA with equal contribution {shicheng@cs.stanford.edu}; (3) Theo Culhane, Computer Science Department, Stanford University Stanford, CA {tculhane@cs.stanford.edu}; (4) Elizaveta Pertseva, Computer Science Department, Stanford University Stanford, CA, {pertseva@cs.stanford.edu}; (5) Meng-Hsi Wu, … Read more